From what I've seen in the RSEM documentation/output examples, I will have to manually apply calculations to normalize triplicate samples, and to determine expression change between samples. I may need help in that area.
I still may try to create a fake transcripts.gtf file for cufflinks. A Newbler assembly using just 454 reads usually creates isogroups(genes) where ~70% are single transcript. These can easily be entered into the transcript.gtf file using fake genomic coordinates. And I suspect that around 30% of multi-transcript isogroups are retrotransposons. The rest of the isogroups I can throwout if they are irrelevant genes (such as housekeeping), or I can align them to best match rice(close relative where genome has been sequenced) transcripts to determine where exons/overlaps potentially are. Does this sound rational?
I still may try to create a fake transcripts.gtf file for cufflinks. A Newbler assembly using just 454 reads usually creates isogroups(genes) where ~70% are single transcript. These can easily be entered into the transcript.gtf file using fake genomic coordinates. And I suspect that around 30% of multi-transcript isogroups are retrotransposons. The rest of the isogroups I can throwout if they are irrelevant genes (such as housekeeping), or I can align them to best match rice(close relative where genome has been sequenced) transcripts to determine where exons/overlaps potentially are. Does this sound rational?
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